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Performance of SVM based regression models on various input features on 163 natural peptide dataset.

Figshare2018-06-01 更新2026-04-29 收录

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https://figshare.com/articles/dataset/Performance_of_SVM_based_regression_models_on_various_input_features_on_163_natural_peptide_dataset_/6403916 数据链接链接失效反馈

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Performance of SVM based regression models on various input features on 163 natural peptide dataset.

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2018-06-01

肽性质预测

分类器性能评估

*Comparison of AUC and accuracy when the classifier was 10-fold cross-validated on all the peptides in the original training set, or on peptides that the first classifier classified correctly (1st deg

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Chemical-Functional Diversity in Cell-Penetrating Peptides

肽性质预测

药物递送载体设计

Cell-penetrating peptides (CPPs) are a promising tool to overcome cell membrane barriers. They have already been successfully applied as carriers for several problematic cargoes, like e.g. plasmid DNA

NIAID Data Ecosystem60

Five amino acid scales used for the features construction.

肽性质预测

氨基酸特征工程

Columns 2–6 report five of the most promising amino acid properties for predicting the peptide reactivity: antigenicity [9], accessibility [10], hydrophilicity [11], flexibility [12] and predicted bet

Figshare2015-12-02 更新20

The detailed results of model comparison between basline models and pepMTL in RT, CCS, MS/MS prediction

肽性质预测

质谱分析

This is a record file of the running results of the pepMTL model in the article "pepMTL: a synchronous multi-properties predictor for peptides enabled by multi-task framework and pre-trained protein l

Figshare2024-03-22 更新70

ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics

蛋白质组学

肽性质预测

Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled

NIAID Data Ecosystem50

Performance of SVM based regression models on various input features on 163 natural peptide dataset.

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